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Troubleshooting

PT | EN

Guide to solving the most frequent problems during installation, configuration, and use of Vectora.

Installation

Error: npm: command not found

Cause: Node.js is not installed or not in your PATH.

Solution:

# Install Node.js: https://nodejs.org (LTS recommended)
node --version # Should return v18+
npm --version # Should return 9+

Error: EACCES: permission denied

Cause: Insufficient permission to install globally.

Solution:

# Configure npm for local installation
mkdir ~/.npm-global
npm config set prefix '~/.npm-global'
export PATH=~/.npm-global/bin:$PATH

# Add the line above to your ~/.bashrc or ~/.zshrc
npm install -g @kaffyn/vectora

Error: vectora: command not found

Cause: Vectora is installed but not in your PATH.

Solution:

# Verify installation
npm list -g @kaffyn/vectora

# Reinstall
npm install -g @kaffyn/vectora

# Test
vectora --version

Configuration

Error: API key not found

Cause: Environment variables not configured.

Solution:

# Verify if keys are defined
echo $GEMINI_API_KEY
echo $VOYAGE_API_KEY

# If empty, configure
export GEMINI_API_KEY="your_key_here"
export VOYAGE_API_KEY="your_key_here"

# Or create a .env file
cat > .env << 'EOF'
GEMINI_API_KEY=sk-xxx
VOYAGE_API_KEY=pa-xxx
EOF

Error: Config validation failed

Cause: Invalid YAML syntax in vectora.config.yaml.

Solution:

# Validate YAML
yamllint vectora.config.yaml

# Or use online: https://yamllint.com

# Common errors:
# - Inconsistent indentation (use 2 spaces)
# - Missing quotes around values
# - Unescaped special symbols

Error: Trust folder does not exist

Cause: The path in trust_folder does not exist.

Solution:

# Update vectora.config.yaml
namespace:
  trust_folder: "." # or a valid path

MCP Integration

Error: Vectora MCP server not found

Cause: claude_desktop_config.json is poorly formatted.

Solution:

{
  "mcpServers": {
    "vectora": {
      "command": "vectora",
      "args": ["mcp-serve"]
    }
  }
}

Verify:

  • JSON is valid (use jsonlint.com)
  • File is in correct location: ~/.claude/claude_desktop_config.json
  • Restart Claude Desktop after saving

Error: Connection refused

Cause: Vectora cannot connect to the API.

Solution:

# Verify API keys
echo $GEMINI_API_KEY
echo $VOYAGE_API_KEY

# Test connectivity
curl https://generativelanguage.googleapis.com/v1beta/models

# If it fails, your key might be invalid
# Generate a new key at https://aistudio.google.com/app/apikey

Claude does not use Vectora automatically

Cause: Claude does not detect that the tool is relevant.

Solution: Be explicit in your request:

Use Vectora to search for context about authentication.
Search the codebase for JWT implementations.

API & Providers

Error: 403 Quota Exceeded (Gemini)

Cause: Request limit exceeded (60/min on free tier).

Solution:

# Wait for quota reset (next minute)
# Or upgrade to Plus plan at https://vectora.dev/plans

# For debug: verify usage
vectora stats --provider gemini

Error: 401 Unauthorized (Voyage)

Cause: API key invalid or expired.

Solution:

# Generate new key at https://dash.voyageai.com/api-keys
vectora config set --key VOYAGE_API_KEY --value "new_key"

# Test
vectora test --provider voyage

Error: Network timeout

Cause: Slow connection or API unavailable.

Solution:

# Increase timeout (default: 30s)
export VECTORA_TIMEOUT_MS=60000

# Test connectivity
ping generativelanguage.googleapis.com

# If using VPN/proxy:
export HTTP_PROXY=http://proxy:port
export HTTPS_PROXY=https://proxy:port

Indexing & RAG

Error: Project not found

Cause: Namespace does not exist.

Solution:

# Initialize project
vectora init --name "My Project"

# Or specify in claude_desktop_config.json
"VECTORA_NAMESPACE": "my-project"

Error: No results found

Cause: Codebase not indexed or irrelevant query.

Solution:

# Force reindexing
vectora ingest --project . --force

# Verify status
vectora status --project .

# Try a different or more specific query
# Example: instead of "auth", try "JWT validation in middleware"

Very slow embedding

Cause: Large codebase or slow connection.

Solution:

# Use batch processing
vectora ingest --batch-size 16 # default: 32

# Or configure in vectora.config.yaml
indexing:
  batch_size: 16

# For local development, use fallback
providers:
  embedding:
    fallback: "local" # local embedding via ollama

Performance

Claude Desktop is slow

Cause: Too many simultaneous requests or large codebase.

Solution:

# Limit automatic indexing
vectora config set VECTORA_AUTO_INGEST=false

# Or schedule indexing for off-peak times
vectora schedule ingest --time 02:00 --recurring daily

High memory usage

Cause: Large local cache or uncleaned indices.

Solution:

# Clear cache
vectora cache clear

# Reduce cache size
vectora config set VECTORA_CACHE_SIZE=100MB

# Verify consumption
vectora stats --memory

Debug & Logging

Activate debug mode

# Via CLI
vectora --log-level debug

# Via variable
export VECTORA_LOG_LEVEL=debug

# Save logs to file
vectora mcp-serve --log-file debug.log

Get more information

# General status
vectora status

# Configuration details
vectora config list

# Usage statistics
vectora stats

# Verify indexing
vectora index --list --verbose

Where to Seek Help

  1. Specific FAQs:

  2. Documentation:

  3. Community:

  4. Report Bug:

    vectora bug-report --include-logs --include-config
    # Generates file with sanitized information to send

FAQ

Q: Where is my data? A: Locally in .vectora/ (cache) and Qdrant (indexed embeddings). Kaffyn never accesses your raw code.

Q: How to reset everything? A: Use vectora reset --full --confirm. This removes cache, indices, and local config.

Q: Can I use Vectora without internet? A: Partially. Semantic search needs an API. File operations work offline.


Part of the Vectora ecosystem · Open Source (MIT) · Contributors